Here’s the translation of the provided Persian text into English:
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What is Artificial Intelligence and How Does It Work?
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#Artificial_Intelligence (AI) refers to the ability of a computer system to imitate human cognitive functions, such as learning, reasoning, and problem-solving.
In other words, it’s an effort to build machines that can perform tasks that usually require human intelligence.
Artificial intelligence is a broad field that includes various approaches, including machine learning, neural networks, natural language processing, and expert systems.
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Machine Learning is a core method in artificial intelligence that allows machines to learn from data without explicit programming.
This process involves training a model using large datasets to identify patterns and relationships and make predictions or decisions based on them.
Machine learning algorithms are used in a wide range of applications, from image and speech recognition to filtering spam emails and product recommendations.
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Neural Networks are computational models inspired by the structure of the human brain.
They are composed of interconnected nodes (neurons) that process and transmit information.
Neural networks have performed very well in tasks such as image recognition, natural language processing, and computer games.
One important type of neural network is deep neural networks, which use multiple layers of neurons and are capable of learning complex patterns in data.
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Natural Language Processing (NLP) is a branch of artificial intelligence that allows machines to understand and process human language.
NLP includes tasks such as machine translation, sentiment analysis, text summarization, and question answering.
Using NLP, machines can communicate with humans in natural language and extract information from text.
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Expert Systems are computer programs that mimic the knowledge and skills of a human expert in a specific field.
These systems typically use a knowledge base and an inference engine to reason and make decisions based on existing knowledge.
Expert systems are used in applications such as medical diagnosis, financial planning, and control of industrial processes.
Artificial intelligence is rapidly advancing and is expected to play an increasingly important role in our lives in the future.
Wikipedia can provide you with useful information.
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Applications of Artificial Intelligence in Various Industries
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Artificial intelligence currently has widespread applications in various industries and helps to improve efficiency, reduce costs, and create new opportunities.
Here are some of these applications:
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Healthcare Artificial intelligence is used in disease diagnosis, drug development, patient care, and hospital management.
Machine learning algorithms can analyze medical images and detect early signs of diseases.
Also, artificial intelligence can help design new drugs and optimize treatment plans.
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Finance In the financial industry, artificial intelligence is used in fraud detection, risk management, algorithmic trading, and customer service.
Machine learning algorithms can identify suspicious patterns in financial transactions and prevent fraud.
Also, artificial intelligence can help in providing personal financial advice and managing investment portfolios.
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Manufacturing Artificial intelligence is used in automating manufacturing processes, quality control, predicting equipment failure, and optimizing the supply chain.
Intelligent robots can perform repetitive and dangerous tasks, while machine learning algorithms can identify product defects and prevent the production of substandard products.
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Transportation Artificial intelligence is used in self-driving cars, route optimization, traffic management, and providing intelligent transportation services.
Self-driving cars use sensors and artificial intelligence algorithms to understand their surroundings and drive safely.
Also, artificial intelligence can help optimize transportation routes and reduce traffic.
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Retail Artificial intelligence is used in providing personalized shopping experiences, predicting demand, managing inventory, and providing customer service.
Recommendation systems can suggest products that customers are interested in, while machine learning algorithms can predict product demand and help optimize inventory.
Artificial intelligence is transforming various industries and is expected to find more applications in the future.
Specialized AI website provides more information in this field.
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Machine Learning and its Role in the Development of Artificial Intelligence
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Machine learning is one of the main branches of artificial intelligence and plays a very important role in the development of intelligent systems.
This approach allows machines to learn from data and improve their performance without explicit programming.
Machine learning algorithms are used in a wide range of applications, from image and speech recognition to prediction and decision-making.
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Types of Machine Learning
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- Supervised Learning In this method, the machine is trained using labeled datasets.
Each sample in the dataset includes an input and an expected output.
The goal is for the machine to learn how to map inputs to corresponding outputs. - Unsupervised Learning In this method, the machine is trained using unlabeled datasets.
The goal is for the machine to identify hidden patterns and structures in the data.
Clustering and dimensionality reduction are common techniques in unsupervised learning. - Reinforcement Learning In this method, the machine learns how to optimize a goal by interacting with an environment.
The machine learns the optimal strategy by performing different actions in the environment and receiving rewards or penalties.
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Applications of Machine Learning
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- Image Recognition Machine learning algorithms can analyze images and recognize objects, faces, and various patterns.
- Natural Language Processing Machine learning is used in machine translation, sentiment analysis, text summarization, and question answering.
- Prediction Machine learning algorithms can analyze data and predict future trends.
- Decision Making Machine learning can be used in automated decision-making in various fields such as finance, marketing, and manufacturing.
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Machine learning, as a powerful tool in the development of artificial intelligence, is expanding and is expected to play an increasingly important role in our lives in the future.
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| Machine Learning Type | Description |
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| Supervised Learning | Training with labeled data |
| Unsupervised Learning | Identifying patterns in unlabeled data |
| Reinforcement Learning | Learning through interaction with the environment |
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Natural Language Processing and Machine Language Understanding
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Natural Language Processing (NLP) is a branch of artificial intelligence that allows machines to understand and process human language.
NLP includes tasks such as machine translation, sentiment analysis, text summarization, and question answering.
Using NLP, machines can communicate with humans in natural language and extract information from text.
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Challenges of Natural Language Processing
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- Ambiguity Human language is often ambiguous, and a word or sentence can have different meanings.
- Diversity Human language is very diverse, and there are different dialects, accents, and styles.
- Knowledge Understanding human language requires knowledge of the world and context.
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Techniques of Natural Language Processing
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- Parsing Parsing involves analyzing the grammatical structure of a sentence and identifying its components.
- Semantics Semantics involves understanding the meaning of words and sentences.
- Pragmatics Pragmatics involves understanding the purpose and context of a sentence.
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Applications of Natural Language Processing
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- Machine Translation Machine translation allows machines to translate text from one language to another.
- Sentiment Analysis Sentiment analysis allows machines to identify the emotions and attitudes present in the text.
- Text Summarization Text summarization allows machines to generate a summary of a long text.
- Question Answering Question answering allows machines to answer questions posed in natural language.
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Natural language processing, as an active field in artificial intelligence, is progressing and is expected to play an increasingly important role in the interaction between humans and machines in the future.
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The Future of Artificial Intelligence and its Impact on Human Life
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Artificial intelligence is rapidly advancing and is expected to play an increasingly important role in our lives in the future.
On the one hand, artificial intelligence can help solve complex problems, improve efficiency, and create new opportunities.
On the other hand, there are concerns about the impact of artificial intelligence on employment, privacy, and security.
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Positive Impacts of Artificial Intelligence
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- Improving Healthcare Artificial intelligence can help in disease diagnosis, drug development, and patient care.
- Increasing Efficiency Artificial intelligence can automate production, transportation, and management processes and increase efficiency.
- Creating New Opportunities Artificial intelligence can create new opportunities in various fields such as education, entertainment, and art.
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Concerns about Artificial Intelligence
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- Job Loss Automation caused by artificial intelligence can lead to job losses in some industries.
- Privacy The collection and analysis of data by artificial intelligence systems can create privacy concerns.
- Security Artificial intelligence can be used in cyber attacks and the construction of automated weapons.
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Ethical Issues related to Artificial Intelligence
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- Bias Artificial intelligence algorithms can be biased based on their training data.
- Transparency The decision-making of artificial intelligence systems may be inexplicable.
- Responsibility Determining responsibility in the event of an error by artificial intelligence systems is difficult.
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To benefit from the advantages of artificial intelligence and reduce its risks, we need to develop appropriate policies and regulations, train the workforce, and pay attention to ethical issues.
AI Ethics Reference provides useful solutions.
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Neural Networks and Deep Learning
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Neural networks are computational models inspired by the structure of the human brain.
They are composed of interconnected nodes (neurons) that process and transmit information.
Neural networks have performed very well in tasks such as image recognition, natural language processing, and computer games.
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Deep Learning is a subset of machine learning that uses deep neural networks (neural networks with multiple layers).
Deep neural networks are capable of learning complex patterns in data and have performed very well in tasks such as image recognition, natural language processing, and content generation.
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Types of Neural Networks
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- Feedforward Neural Networks In this type of network, information only flows in one direction (from input to output).
- Recurrent Neural Networks In this type of network, information can return to previous nodes.
Recurrent neural networks are suitable for processing sequential data such as text and sound. - Convolutional Neural Networks In this type of network, convolutional layers are used to extract features from the data.
Convolutional neural networks are suitable for image recognition.
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Applications of Neural Networks and Deep Learning
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- Image Recognition Neural networks can analyze images and recognize objects, faces, and various patterns.
- Natural Language Processing Neural networks are used in machine translation, sentiment analysis, text summarization, and question answering.
- Content Generation Neural networks can generate text, images, sound, and video.
- Computer Games Neural networks can be used in computer games as players or opponents.
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Neural networks and deep learning, as powerful tools in artificial intelligence, are expanding and are expected to play an increasingly important role in our lives in the future.
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Challenges and Limitations of Artificial Intelligence
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Artificial intelligence, despite significant progress, still faces numerous challenges and limitations.
These challenges include technical, ethical, and social issues and require attention and appropriate solutions.
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Technical Challenges
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- Need for Big Data Machine learning algorithms require a large amount of data for training.
Collecting and labeling this data can be time-consuming and costly. - Interpretability The decision-making of artificial intelligence systems may be inexplicable.
This can reduce trust in these systems. - Transferability An artificial intelligence model that performs well in one field may perform poorly in another field.
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Ethical Challenges
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- Bias Artificial intelligence algorithms can be biased based on their training data.
This can lead to discrimination. - Privacy The collection and analysis of data by artificial intelligence systems can create privacy concerns.
- Responsibility Determining responsibility in the event of an error by artificial intelligence systems is difficult.
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Social Challenges
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- Job Loss Automation caused by artificial intelligence can lead to job losses in some industries.
- Inequality Artificial intelligence can exacerbate social inequalities.
- Security Artificial intelligence can be used in cyber attacks and the construction of automated weapons.
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To overcome these challenges, we need more research and development, the development of ethical and legal standards, and workforce training.
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| Challenge Type | Description |
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| Technical | Need for big data, interpretability, transferability |
| Ethical | Bias, privacy, responsibility |
| Social | Job loss, inequality, security |
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The Role of Governments and Organizations in the Development and Regulation of Artificial Intelligence
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Governments and organizations play an important role in the development and regulation of artificial intelligence.
They can help realize the benefits of artificial intelligence and reduce its risks by investing in research and development, developing ethical and legal standards, and training the workforce.
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Government Actions
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- Investing in Research and Development Governments can help develop this technology by allocating budgets to research projects in the field of artificial intelligence.
- Developing Ethical and Legal Standards Governments can prevent the misuse of artificial intelligence by developing ethical and legal standards.
- Workforce Training Governments can help the workforce prepare for new jobs in the field of artificial intelligence by providing skills training.
- Supporting Start-up Businesses Governments can help start-up businesses in the field of artificial intelligence by providing financial and legal facilities.
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Organization Actions
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- Developing Ethical Standards Organizations can help use artificial intelligence responsibly by developing ethical standards.
- Staff Training Organizations can help their employees use artificial intelligence effectively by providing skills training.
- Cooperation with Governments and Other Organizations Organizations can help develop and regulate artificial intelligence by cooperating with governments and other organizations.
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By cooperating governments and organizations, artificial intelligence can be used as a powerful tool to improve human life.
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Skills Needed to Enter the Field of Artificial Intelligence
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Entering the field of artificial intelligence requires a combination of technical, analytical, and creative skills.
These skills help you have a deep understanding of artificial intelligence concepts and be able to effectively participate in artificial intelligence projects.
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Technical Skills
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- Programming Proficiency in programming languages such as Python, Java, and R is essential for developing artificial intelligence algorithms and models.
- Mathematics and Statistics A strong knowledge in the fields of mathematics and statistics is essential for understanding the concepts of machine learning and natural language processing.
- Machine Learning Familiarity with machine learning algorithms and methods of model evaluation is essential.
- Natural Language Processing Familiarity with natural language processing techniques and methods of extracting information from text is essential.
- Data Engineering Skill in collecting, cleaning, and analyzing data is essential for training artificial intelligence models.
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Analytical Skills
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- Problem Solving The ability to solve complex problems using analytical and creative methods is essential.
- Critical Thinking The ability to evaluate information and make logical decisions is essential.
- Attention to Detail Accuracy in work and attention to detail are essential for developing accurate and reliable artificial intelligence models.
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Soft Skills
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- Teamwork The ability to work as part of a team and cooperate with other professionals is essential.
- Communication The ability to communicate effectively with other people and present ideas clearly and concisely is essential.
- Continuous Learning Artificial intelligence is an evolving field, so the ability to learn continuously and update knowledge is essential.
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By acquiring these skills, you can effectively operate in the field of artificial intelligence and help develop this technology.
Explore Career Paths in AI.
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Educational Resources for Learning Artificial Intelligence
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There are numerous educational resources for learning artificial intelligence that you can use to acquire the necessary knowledge and skills.
These resources include online courses, books, blogs, scientific articles, and online forums.
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Online Courses
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- Coursera Coursera offers numerous courses in the field of artificial intelligence, machine learning, and natural language processing.
- edX edX offers numerous courses in the field of artificial intelligence from top universities in the world.
- Udacity Udacity offers specialized courses in the field of artificial intelligence that help you acquire the practical skills needed to enter this field.
- Khan Academy Khan Academy offers free courses in the field of mathematics, statistics, and computer science that are essential for learning artificial intelligence.
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Books
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- Artificial Intelligence: A Modern Approach This book is a comprehensive introduction to artificial intelligence and fully covers the main concepts of this field.
- Machine Learning This book addresses machine learning algorithms and methods of model evaluation.
- Natural Language Processing This book addresses natural language processing techniques and methods of extracting information from text.
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Blogs and Scientific Articles
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- Medium Medium offers numerous articles in the field of artificial intelligence from different authors.
- arXiv arXiv is an online archive of scientific articles in the field of computer science and artificial intelligence.
- Journal of Artificial Intelligence Research Journal of Artificial Intelligence Research is a reputable scientific journal in the field of artificial intelligence.
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Online Forums
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- Stack Overflow Stack Overflow is an online forum for programmers where you can ask your questions about artificial intelligence.
- Reddit Reddit is an online forum where you can discuss and exchange ideas about artificial intelligence with other people.
- Kaggle Kaggle is an online platform for competing in machine learning projects.
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By using these educational resources, you can acquire the necessary knowledge and skills to enter the field of artificial intelligence and help develop this technology.
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FAQ
| Question | Answer |
|---|---|
| What is the definition of Artificial Intelligence (AI)? | It is a field in computer science that aims to create intelligent machines that can think, learn, solve problems, and make decisions like humans. |
| Mention some common applications of artificial intelligence. | Includes self-driving cars, voice assistants (such as Siri and Alexa), recommendation systems (such as Netflix and Amazon), facial recognition, and medical diagnosis. |
| What is the difference between Narrow Artificial Intelligence (ANI) and General Artificial Intelligence (AGI)? | Narrow Artificial Intelligence is specialized in one specific task, while General Artificial Intelligence possesses human intellectual ability to perform any cognitive task. |
| What is Machine Learning and its relationship to Artificial Intelligence? | Machine Learning is a branch of Artificial Intelligence that focuses on developing algorithms that allow systems to learn from data without explicit programming. |
| What are Artificial Neural Networks? | They are computational models inspired by the structure and function of the human brain and are used in deep learning to process data and discover complex patterns. |
| Mention some ethical challenges related to Artificial Intelligence. | Includes issues of privacy, bias in data and algorithms, job loss, and responsibility in case of errors or unfair decisions. |
| What is Natural Language Processing (NLP)? | It is a branch of Artificial Intelligence that focuses on enabling computers to understand, interpret, and generate human language in a useful and interactive manner. |
| How can Artificial Intelligence affect the labor market? | It can lead to the automation of some routine tasks, requiring retraining of workers and creating new jobs in the fields of designing, developing, and maintaining Artificial Intelligence systems. |
| What is Computer Vision? | It is a field in Artificial Intelligence that enables computers to “see,” understand, and interpret images and videos in the same way that humans do, enabling them to recognize objects and faces. |
| What is the importance of data in developing Artificial Intelligence systems? | Data is the fuel that feeds Artificial Intelligence systems, especially in machine learning. The quality and quantity of data significantly affect the accuracy and performance of models and their ability to learn and make correct decisions. |
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References
Artificial intelligence in Iran
,What are the applications of artificial intelligence from the perspective of women and what happens
, What is artificial intelligence?
,Narratives and effects of artificial intelligence in today’s life
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